Bioconductor DES

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368

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DESeq2 RUVSeq RUVseq BatchEffect DES

updated 9 days ago by James W. MacDonald 65k • written 9 days ago by Alexandre • 0

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132

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Des DESeq2

updated 22 days ago by hemantcnaik • 0 • written 22 days ago by Sahar • 0

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219

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DESeq2 DEs

7 weeks ago • updated 6 weeks ago feather-W • 0

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508

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DESeq2 des

updated 17 months ago by Michael Love 41k • written 18 months ago by Devin • 0

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567

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DES DESIGN

updated 19 months ago by Michael Love 41k • written 19 months ago by mike • 0

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617

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DESeq2 DES

updated 3.4 years ago by Michael Love 41k • written 3.4 years ago by heikki.sarin ▴ 10

6 results • Page 1 of 1

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Answer: How to use bootRanges to bootstrap small RNA loci (nullranges package) by Poonam • 0

Hi Michael, I think there is something wrong with the generation of nullranges. I was working with small RNA and methylation overlaps. …

Answer: Once again a "Model matrix not full rank" by swbarnes2 ★ 1.3k

Replicate numbers, like the 1 in control_1 are fine in sample names, but never add them to anything else in colData. From the computer's p…

Answer: limma Intercept vs No-intercept models completely changing DMR results? by Gordon Smyth 50k

I'll add a little bit of general advice to James' answer. You seem to have the misunderstanding that you can change the design matrix but …

Answer: package goseq seems to be not available on the latest version of R by Gordon Smyth 50k

It is true that goseq isn't available for Bioc 3.19. That is because goseq depends on txbmaker, which is itself not yet available for Bioc…

Answer: limma Intercept vs No-intercept models completely changing DMR results? by James W. MacDonald 65k

This part: ``` design_intercept <- model.matrix(~Alt+Sex+Age+PC1, data=targets_Sherpa) colnames(design_intercept) <- c("AltSHP_LA","Al…

Votes

Answer: Why does GSEA on edgeR results for randomized samples give highly significant p-

Answer: limma Intercept vs No-intercept models completely changing DMR results?

Answer: CombineArrays for EPIC and EPIC V2

Answer: Too many significant genes when integrating gtex and tcga

Comment: Too many significant genes when integrating gtex and tcga

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